AI is rapidly changing the landscape of hospital analytics. Data may be processed quicker, and analytics generated with greater ease than ever before. However, AI cannot fix the most important things – the data that’s available and the accuracy of that data.

Hospitals continue to struggle to capture the data that would allow for the greatest insights into operational planning and management – and are frequently unable to differentiate between what SHOULD happen and what DID happen –the real waits and delays that exist, and the true potential impact of process improvement. Is your hospital able to accurately track wait times along the care pathway?

As you undertake any AI implementations, let the Institute for Healthcare Optimization help you understand how to get the most out of your analytics, by evaluating both WHAT data is needed and HOW to capture it to ensure the best insights. Schedule a call to learn more >>

When planning to implement smoothing of your elective surgical schedule, it is critical set your organization up for success to fully optimize scheduling to improve patient throughput and access. The following are some of the most important pieces to identify:

•  Patient type: Only elective (scheduled) patients can be smoothed, making them the ideal population for scheduling algorithms designed to reduce avoidable peaks.

•  Demand categorization: Patients who require similar downstream resources should be smoothed as a group — for example, elective admissions that will need beds on post-op ICU, cardiac, or orthopedic units.

•  Expected length of stay or visit length: Projecting length of stay accurately at the time of booking helps hospitals match demand to available beds, staff, and procedural capacity across the week.

•  Timely communication: Smoothing only works when planned admissions, bed needs, discharge expectations, and staffing implications are shared early and consistently across perioperative teams, inpatient units, and case management.

IHO has worked with numerous hospitals to ensure they have the data to get surgical smoothing implementation right.